Morten Hjorth-Jensen
406 lines
25 KiB
HTML
406 lines
25 KiB
HTML
<!--
|
|
HTML file automatically generated from DocOnce source
|
|
(https://github.com/doconce/doconce/)
|
|
doconce format html week47.do.txt --html_style=bootstrap --pygments_html_style=default --html_admon=bootstrap_panel --html_output=week47-bs --no_mako
|
|
-->
|
|
<html>
|
|
<head>
|
|
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
|
<meta name="generator" content="DocOnce: https://github.com/doconce/doconce/" />
|
|
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
|
<meta name="description" content="Week 47: Support Vector Machines and Summary of Course">
|
|
<title>Week 47: Support Vector Machines and Summary of Course</title>
|
|
<!-- Bootstrap style: bootstrap -->
|
|
<!-- doconce format html week47.do.txt --html_style=bootstrap --pygments_html_style=default --html_admon=bootstrap_panel --html_output=week47-bs --no_mako -->
|
|
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
|
<!-- not necessary
|
|
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
|
-->
|
|
<style type="text/css">
|
|
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
|
.dropdown-menu {
|
|
height: auto;
|
|
max-height: 400px;
|
|
overflow-x: hidden;
|
|
}
|
|
/* Adds an invisible element before each target to offset for the navigation
|
|
bar */
|
|
.anchor::before {
|
|
content:"";
|
|
display:block;
|
|
height:50px; /* fixed header height for style bootstrap */
|
|
margin:-50px 0 0; /* negative fixed header height */
|
|
}
|
|
</style>
|
|
</head>
|
|
|
|
<!-- tocinfo
|
|
{'highest level': 2,
|
|
'sections': [('Overview of week 47', 2, None, 'overview-of-week-47'),
|
|
('Support Vector Machines, overarching aims',
|
|
2,
|
|
None,
|
|
'support-vector-machines-overarching-aims'),
|
|
('Hyperplanes and all that', 2, None, 'hyperplanes-and-all-that'),
|
|
('What is a hyperplane?', 2, None, 'what-is-a-hyperplane'),
|
|
('A $p$-dimensional space of features',
|
|
2,
|
|
None,
|
|
'a-p-dimensional-space-of-features'),
|
|
('The two-dimensional case', 2, None, 'the-two-dimensional-case'),
|
|
('Getting into the details', 2, None, 'getting-into-the-details'),
|
|
('First attempt at a minimization approach',
|
|
2,
|
|
None,
|
|
'first-attempt-at-a-minimization-approach'),
|
|
('Solving the equations', 2, None, 'solving-the-equations'),
|
|
('Problems with the Simpler Approach',
|
|
2,
|
|
None,
|
|
'problems-with-the-simpler-approach'),
|
|
('A better approach', 2, None, 'a-better-approach'),
|
|
('A quick Reminder on Lagrangian Multipliers',
|
|
2,
|
|
None,
|
|
'a-quick-reminder-on-lagrangian-multipliers'),
|
|
('Adding the Multiplier', 2, None, 'adding-the-multiplier'),
|
|
('Setting up the Problem', 2, None, 'setting-up-the-problem'),
|
|
('The problem to solve', 2, None, 'the-problem-to-solve'),
|
|
('The last steps', 2, None, 'the-last-steps'),
|
|
('A soft classifier', 2, None, 'a-soft-classifier'),
|
|
('Soft optmization problem', 2, None, 'soft-optmization-problem'),
|
|
('Kernels and non-linearity',
|
|
2,
|
|
None,
|
|
'kernels-and-non-linearity'),
|
|
('The equations', 2, None, 'the-equations'),
|
|
('The problem to solve', 2, None, 'the-problem-to-solve'),
|
|
("Different kernels and Mercer's theorem",
|
|
2,
|
|
None,
|
|
'different-kernels-and-mercer-s-theorem'),
|
|
('The moons example', 2, None, 'the-moons-example'),
|
|
('Mathematical optimization of convex functions',
|
|
2,
|
|
None,
|
|
'mathematical-optimization-of-convex-functions'),
|
|
('How do we solve these problems?',
|
|
2,
|
|
None,
|
|
'how-do-we-solve-these-problems'),
|
|
('A simple example', 2, None, 'a-simple-example'),
|
|
('Support Vector Machines and Regression',
|
|
2,
|
|
None,
|
|
'support-vector-machines-and-regression'),
|
|
('Summary of course', 2, None, 'summary-of-course'),
|
|
('What? Me worry? No final exam in this course!',
|
|
2,
|
|
None,
|
|
'what-me-worry-no-final-exam-in-this-course'),
|
|
('What is the link between Artificial Intelligence and Machine '
|
|
'Learning and some general Remarks',
|
|
2,
|
|
None,
|
|
'what-is-the-link-between-artificial-intelligence-and-machine-learning-and-some-general-remarks'),
|
|
('Going back to the beginning of the semester',
|
|
2,
|
|
None,
|
|
'going-back-to-the-beginning-of-the-semester'),
|
|
('Not so sharp distinctions',
|
|
2,
|
|
None,
|
|
'not-so-sharp-distinctions'),
|
|
('Topics we have covered this year',
|
|
2,
|
|
None,
|
|
'topics-we-have-covered-this-year'),
|
|
('Statistical analysis and optimization of data',
|
|
2,
|
|
None,
|
|
'statistical-analysis-and-optimization-of-data'),
|
|
('Machine learning', 2, None, 'machine-learning'),
|
|
('Learning outcomes and overarching aims of this course',
|
|
2,
|
|
None,
|
|
'learning-outcomes-and-overarching-aims-of-this-course'),
|
|
('Perspective on Machine Learning',
|
|
2,
|
|
None,
|
|
'perspective-on-machine-learning'),
|
|
('Machine Learning Research',
|
|
2,
|
|
None,
|
|
'machine-learning-research'),
|
|
('Starting your Machine Learning Project',
|
|
2,
|
|
None,
|
|
'starting-your-machine-learning-project'),
|
|
('Choose a Model and Algorithm',
|
|
2,
|
|
None,
|
|
'choose-a-model-and-algorithm'),
|
|
('Preparing Your Data', 2, None, 'preparing-your-data'),
|
|
('Which Activation and Weights to Choose in Neural Networks',
|
|
2,
|
|
None,
|
|
'which-activation-and-weights-to-choose-in-neural-networks'),
|
|
('Optimization Methods and Hyperparameters',
|
|
2,
|
|
None,
|
|
'optimization-methods-and-hyperparameters'),
|
|
('Resampling', 2, None, 'resampling'),
|
|
('Other courses on Data science and Machine Learning at UiO',
|
|
2,
|
|
None,
|
|
'other-courses-on-data-science-and-machine-learning-at-uio'),
|
|
('Additional courses of interest',
|
|
2,
|
|
None,
|
|
'additional-courses-of-interest'),
|
|
("What's the future like?", 2, None, 'what-s-the-future-like'),
|
|
('Types of Machine Learning, a repetition',
|
|
2,
|
|
None,
|
|
'types-of-machine-learning-a-repetition'),
|
|
('Why Boltzmann machines?', 2, None, 'why-boltzmann-machines'),
|
|
('Boltzmann Machines', 2, None, 'boltzmann-machines'),
|
|
('Some similarities and differences from DNNs',
|
|
2,
|
|
None,
|
|
'some-similarities-and-differences-from-dnns'),
|
|
('Boltzmann machines (BM)', 2, None, 'boltzmann-machines-bm'),
|
|
('A standard BM setup', 2, None, 'a-standard-bm-setup'),
|
|
('The structure of the RBM network',
|
|
2,
|
|
None,
|
|
'the-structure-of-the-rbm-network'),
|
|
('The network', 2, None, 'the-network'),
|
|
('Goals', 2, None, 'goals'),
|
|
('Joint distribution', 2, None, 'joint-distribution'),
|
|
('Network Elements, the energy function',
|
|
2,
|
|
None,
|
|
'network-elements-the-energy-function'),
|
|
('Defining different types of RBMs',
|
|
2,
|
|
None,
|
|
'defining-different-types-of-rbms'),
|
|
('More about RBMs', 2, None, 'more-about-rbms'),
|
|
('Autoencoders: Overarching view',
|
|
2,
|
|
None,
|
|
'autoencoders-overarching-view'),
|
|
('Bayesian Machine Learning',
|
|
2,
|
|
None,
|
|
'bayesian-machine-learning'),
|
|
('Reinforcement Learning', 2, None, 'reinforcement-learning'),
|
|
('Transfer learning', 2, None, 'transfer-learning'),
|
|
('Adversarial learning', 2, None, 'adversarial-learning'),
|
|
('Dual learning', 2, None, 'dual-learning'),
|
|
('Distributed machine learning',
|
|
2,
|
|
None,
|
|
'distributed-machine-learning'),
|
|
('Meta learning', 2, None, 'meta-learning'),
|
|
('The Challenges Facing Machine Learning',
|
|
2,
|
|
None,
|
|
'the-challenges-facing-machine-learning'),
|
|
('Explainable machine learning',
|
|
2,
|
|
None,
|
|
'explainable-machine-learning'),
|
|
('Quantum machine learning', 2, None, 'quantum-machine-learning'),
|
|
('Quantum machine learning algorithms based on linear algebra',
|
|
2,
|
|
None,
|
|
'quantum-machine-learning-algorithms-based-on-linear-algebra'),
|
|
('Quantum reinforcement learning',
|
|
2,
|
|
None,
|
|
'quantum-reinforcement-learning'),
|
|
('Quantum deep learning', 2, None, 'quantum-deep-learning'),
|
|
('Social machine learning', 2, None, 'social-machine-learning'),
|
|
('The last words?', 2, None, 'the-last-words'),
|
|
('Best wishes to you all and thanks so much for your heroic '
|
|
'efforts this semester',
|
|
2,
|
|
None,
|
|
'best-wishes-to-you-all-and-thanks-so-much-for-your-heroic-efforts-this-semester')]}
|
|
end of tocinfo -->
|
|
|
|
<body>
|
|
|
|
|
|
|
|
<script type="text/x-mathjax-config">
|
|
MathJax.Hub.Config({
|
|
TeX: {
|
|
equationNumbers: { autoNumber: "none" },
|
|
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
|
}
|
|
});
|
|
</script>
|
|
<script type="text/javascript" async
|
|
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
|
</script>
|
|
|
|
|
|
<!-- Bootstrap navigation bar -->
|
|
<div class="navbar navbar-default navbar-fixed-top">
|
|
<div class="navbar-header">
|
|
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
|
<span class="icon-bar"></span>
|
|
<span class="icon-bar"></span>
|
|
<span class="icon-bar"></span>
|
|
</button>
|
|
<a class="navbar-brand" href="week47-bs.html">Week 47: Support Vector Machines and Summary of Course</a>
|
|
</div>
|
|
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
|
<ul class="nav navbar-nav navbar-right">
|
|
<li class="dropdown">
|
|
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
|
<ul class="dropdown-menu">
|
|
<!-- navigation toc: --> <li><a href="._week47-bs001.html#overview-of-week-47" style="font-size: 80%;">Overview of week 47</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs002.html#support-vector-machines-overarching-aims" style="font-size: 80%;">Support Vector Machines, overarching aims</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs003.html#hyperplanes-and-all-that" style="font-size: 80%;">Hyperplanes and all that</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs004.html#what-is-a-hyperplane" style="font-size: 80%;">What is a hyperplane?</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs005.html#a-p-dimensional-space-of-features" style="font-size: 80%;">A \( p \)-dimensional space of features</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs006.html#the-two-dimensional-case" style="font-size: 80%;">The two-dimensional case</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs007.html#getting-into-the-details" style="font-size: 80%;">Getting into the details</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs008.html#first-attempt-at-a-minimization-approach" style="font-size: 80%;">First attempt at a minimization approach</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs009.html#solving-the-equations" style="font-size: 80%;">Solving the equations</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs010.html#problems-with-the-simpler-approach" style="font-size: 80%;">Problems with the Simpler Approach</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs011.html#a-better-approach" style="font-size: 80%;">A better approach</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs012.html#a-quick-reminder-on-lagrangian-multipliers" style="font-size: 80%;">A quick Reminder on Lagrangian Multipliers</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs013.html#adding-the-multiplier" style="font-size: 80%;">Adding the Multiplier</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs014.html#setting-up-the-problem" style="font-size: 80%;">Setting up the Problem</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs021.html#the-problem-to-solve" style="font-size: 80%;">The problem to solve</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs016.html#the-last-steps" style="font-size: 80%;">The last steps</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs017.html#a-soft-classifier" style="font-size: 80%;">A soft classifier</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs018.html#soft-optmization-problem" style="font-size: 80%;">Soft optmization problem</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs019.html#kernels-and-non-linearity" style="font-size: 80%;">Kernels and non-linearity</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs020.html#the-equations" style="font-size: 80%;">The equations</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs021.html#the-problem-to-solve" style="font-size: 80%;">The problem to solve</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs022.html#different-kernels-and-mercer-s-theorem" style="font-size: 80%;">Different kernels and Mercer's theorem</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs023.html#the-moons-example" style="font-size: 80%;">The moons example</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs024.html#mathematical-optimization-of-convex-functions" style="font-size: 80%;">Mathematical optimization of convex functions</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs025.html#how-do-we-solve-these-problems" style="font-size: 80%;">How do we solve these problems?</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs026.html#a-simple-example" style="font-size: 80%;">A simple example</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs027.html#support-vector-machines-and-regression" style="font-size: 80%;">Support Vector Machines and Regression</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs028.html#summary-of-course" style="font-size: 80%;">Summary of course</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs029.html#what-me-worry-no-final-exam-in-this-course" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs030.html#what-is-the-link-between-artificial-intelligence-and-machine-learning-and-some-general-remarks" style="font-size: 80%;">What is the link between Artificial Intelligence and Machine Learning and some general Remarks</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs031.html#going-back-to-the-beginning-of-the-semester" style="font-size: 80%;">Going back to the beginning of the semester</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs032.html#not-so-sharp-distinctions" style="font-size: 80%;">Not so sharp distinctions</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs033.html#topics-we-have-covered-this-year" style="font-size: 80%;">Topics we have covered this year</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs034.html#statistical-analysis-and-optimization-of-data" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs035.html#machine-learning" style="font-size: 80%;">Machine learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs036.html#learning-outcomes-and-overarching-aims-of-this-course" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs037.html#perspective-on-machine-learning" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs038.html#machine-learning-research" style="font-size: 80%;">Machine Learning Research</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs039.html#starting-your-machine-learning-project" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs040.html#choose-a-model-and-algorithm" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs041.html#preparing-your-data" style="font-size: 80%;">Preparing Your Data</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs042.html#which-activation-and-weights-to-choose-in-neural-networks" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs043.html#optimization-methods-and-hyperparameters" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs044.html#resampling" style="font-size: 80%;">Resampling</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs045.html#other-courses-on-data-science-and-machine-learning-at-uio" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs046.html#additional-courses-of-interest" style="font-size: 80%;">Additional courses of interest</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs047.html#what-s-the-future-like" style="font-size: 80%;">What's the future like?</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs048.html#types-of-machine-learning-a-repetition" style="font-size: 80%;">Types of Machine Learning, a repetition</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs049.html#why-boltzmann-machines" style="font-size: 80%;">Why Boltzmann machines?</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs050.html#boltzmann-machines" style="font-size: 80%;">Boltzmann Machines</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs051.html#some-similarities-and-differences-from-dnns" style="font-size: 80%;">Some similarities and differences from DNNs</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs052.html#boltzmann-machines-bm" style="font-size: 80%;">Boltzmann machines (BM)</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs053.html#a-standard-bm-setup" style="font-size: 80%;">A standard BM setup</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs054.html#the-structure-of-the-rbm-network" style="font-size: 80%;">The structure of the RBM network</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs055.html#the-network" style="font-size: 80%;">The network</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs056.html#goals" style="font-size: 80%;">Goals</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs057.html#joint-distribution" style="font-size: 80%;">Joint distribution</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs058.html#network-elements-the-energy-function" style="font-size: 80%;">Network Elements, the energy function</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs059.html#defining-different-types-of-rbms" style="font-size: 80%;">Defining different types of RBMs</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs060.html#more-about-rbms" style="font-size: 80%;">More about RBMs</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs061.html#autoencoders-overarching-view" style="font-size: 80%;">Autoencoders: Overarching view</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs062.html#bayesian-machine-learning" style="font-size: 80%;">Bayesian Machine Learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs063.html#reinforcement-learning" style="font-size: 80%;">Reinforcement Learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs064.html#transfer-learning" style="font-size: 80%;">Transfer learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs065.html#adversarial-learning" style="font-size: 80%;">Adversarial learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs066.html#dual-learning" style="font-size: 80%;">Dual learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="#distributed-machine-learning" style="font-size: 80%;">Distributed machine learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs068.html#meta-learning" style="font-size: 80%;">Meta learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs069.html#the-challenges-facing-machine-learning" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs070.html#explainable-machine-learning" style="font-size: 80%;">Explainable machine learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs071.html#quantum-machine-learning" style="font-size: 80%;">Quantum machine learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs072.html#quantum-machine-learning-algorithms-based-on-linear-algebra" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs073.html#quantum-reinforcement-learning" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs074.html#quantum-deep-learning" style="font-size: 80%;">Quantum deep learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs075.html#social-machine-learning" style="font-size: 80%;">Social machine learning</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs076.html#the-last-words" style="font-size: 80%;">The last words?</a></li>
|
|
<!-- navigation toc: --> <li><a href="._week47-bs077.html#best-wishes-to-you-all-and-thanks-so-much-for-your-heroic-efforts-this-semester" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
|
|
|
</ul>
|
|
</li>
|
|
</ul>
|
|
</div>
|
|
</div>
|
|
</div> <!-- end of navigation bar -->
|
|
<div class="container">
|
|
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
|
<a name="part0067"></a>
|
|
<!-- !split -->
|
|
<h2 id="distributed-machine-learning" class="anchor">Distributed machine learning </h2>
|
|
|
|
<p>Distributed computation will speed up machine learning algorithms,
|
|
significantly improve their efficiency, and thus enlarge their
|
|
application. When distributed meets machine learning, more than just
|
|
implementing the machine learning algorithms in parallel is required.
|
|
</p>
|
|
|
|
<p>
|
|
<!-- navigation buttons at the bottom of the page -->
|
|
<ul class="pagination">
|
|
<li><a href="._week47-bs066.html">«</a></li>
|
|
<li><a href="._week47-bs000.html">1</a></li>
|
|
<li><a href="">...</a></li>
|
|
<li><a href="._week47-bs059.html">60</a></li>
|
|
<li><a href="._week47-bs060.html">61</a></li>
|
|
<li><a href="._week47-bs061.html">62</a></li>
|
|
<li><a href="._week47-bs062.html">63</a></li>
|
|
<li><a href="._week47-bs063.html">64</a></li>
|
|
<li><a href="._week47-bs064.html">65</a></li>
|
|
<li><a href="._week47-bs065.html">66</a></li>
|
|
<li><a href="._week47-bs066.html">67</a></li>
|
|
<li class="active"><a href="._week47-bs067.html">68</a></li>
|
|
<li><a href="._week47-bs068.html">69</a></li>
|
|
<li><a href="._week47-bs069.html">70</a></li>
|
|
<li><a href="._week47-bs070.html">71</a></li>
|
|
<li><a href="._week47-bs071.html">72</a></li>
|
|
<li><a href="._week47-bs072.html">73</a></li>
|
|
<li><a href="._week47-bs073.html">74</a></li>
|
|
<li><a href="._week47-bs074.html">75</a></li>
|
|
<li><a href="._week47-bs075.html">76</a></li>
|
|
<li><a href="._week47-bs076.html">77</a></li>
|
|
<li><a href="">...</a></li>
|
|
<li><a href="._week47-bs077.html">78</a></li>
|
|
<li><a href="._week47-bs068.html">»</a></li>
|
|
</ul>
|
|
<!-- ------------------- end of main content --------------- -->
|
|
</div> <!-- end container -->
|
|
<!-- include javascript, jQuery *first* -->
|
|
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
|
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
|
<!-- Bootstrap footer
|
|
<footer>
|
|
<a href="https://..."><img width="250" align=right src="https://..."></a>
|
|
</footer>
|
|
-->
|
|
<center style="font-size:80%">
|
|
<!-- copyright only on the titlepage -->
|
|
</center>
|
|
</body>
|
|
</html>
|
|
|